527 citations · 877 across the 56 of their papers we have counts for
20 papers · 1 filter
Re-basin via implicit Sinkhorn differentiation
Fidel A. Guerrero Peña, Heitor Rapela Medeiros, Thomas Dubail +3
The recent emergence of new algorithms for permuting models into functionally equivalent regions of the solution space has shed some light on the complexity of error surfaces, and…
Multimodal Data Augmentation for Visual-Infrared Person ReID with Corrupted Data
Arthur Josi, Mahdi Alehdaghi, Rafael M. O. Cruz +1
The re-identification (ReID) of individuals over a complex network of cameras is a challenging task, especially under real-world surveillance conditions. Several deep learning mode…
Camera Alignment and Weighted Contrastive Learning for Domain Adaptation in Video Person ReID
Djebril Mekhazni, Maximilien Dufau, Christian Desrosiers +2
Systems for person re-identification (ReID) can achieve a high accuracy when trained on large fully-labeled image datasets. However, the domain shift typically associated with dive…
Privacy-Preserving Person Detection Using Low-Resolution Infrared Cameras
Thomas Dubail, Fidel Alejandro Guerrero Peña, Heitor Rapela Medeiros +3
In intelligent building management, knowing the number of people and their location in a room are important for better control of its illumination, ventilation, and heating with re…
Visible-Infrared Person Re-Identification Using Privileged Intermediate Information
Mahdi Alehdaghi, Arthur Josi, Rafael M. O. Cruz +1
Visible-infrared person re-identification (ReID) aims to recognize a same person of interest across a network of RGB and IR cameras. Some deep learning (DL) models have directly in…
Audio-Visual Fusion for Emotion Recognition in the Valence-Arousal Space Using Joint Cross-Attention
R Gnana Praveen, Eric Granger, Patrick Cardinal
Automatic emotion recognition (ER) has recently gained lot of interest due to its potential in many real-world applications. In this context, multimodal approaches have been shown…
Constrained Sampling for Class-Agnostic Weakly Supervised Object Localization
Shakeeb Murtaza, Soufiane Belharbi, Marco Pedersoli +2
Self-supervised vision transformers can generate accurate localization maps of the objects in an image. However, since they decompose the scene into multiple maps containing variou…
Discriminative Sampling of Proposals in Self-Supervised Transformers for Weakly Supervised Object Localization
Shakeeb Murtaza, Soufiane Belharbi, Marco Pedersoli +2
Drones are employed in a growing number of visual recognition applications. A recent development in cell tower inspection is drone-based asset surveillance, where the autonomous fl…
Hybrid Gromov-Wasserstein Embedding for Capsule Learning
Pourya Shamsolmoali, Masoumeh Zareapoor, Swagatam Das +2
Capsule networks (CapsNets) aim to parse images into a hierarchy of objects, parts, and their relations using a two-step process involving part-whole transformation and hierarchica…
TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained Videos
Soufiane Belharbi, Ismail Ben Ayed, Luke McCaffrey +1
Weakly supervised video object localization (WSVOL) allows locating object in videos using only global video tags such as object class. State-of-art methods rely on multiple indepe…
Enhanced Single-shot Detector for Small Object Detection in Remote Sensing Images
Pourya Shamsolmoali, Masoumeh Zareapoor, Eric Granger +2
Small-object detection is a challenging problem. In the last few years, the convolution neural networks methods have been achieved considerable progress. However, the current detec…
Leveraging Uncertainty for Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images
Soufiane Belharbi, Jérôme Rony, Jose Dolz +3
Trained using only image class label, deep weakly supervised methods allow image classification and ROI segmentation for interpretability. Despite their success on natural images,…
Salient Skin Lesion Segmentation via Dilated Scale-Wise Feature Fusion Network
Pourya Shamsolmoali, Masoumeh Zareapoor, Eric Granger +1
Skin lesion detection in dermoscopic images is essential in the accurate and early diagnosis of skin cancer by a computerized apparatus. Current skin lesion segmentation approaches…
Knowledge Distillation for Multi-Target Domain Adaptation in Real-Time Person Re-Identification
Félix Remigereau, Djebril Mekhazni, Sajjad Abdoli +3
Despite the recent success of deep learning architectures, person re-identification (ReID) remains a challenging problem in real-word applications. Several unsupervised single-targ…
Semi-Weakly Supervised Object Detection by Sampling Pseudo Ground-Truth Boxes
Akhil Meethal, Marco Pedersoli, Zhongwen Zhu +2
Semi- and weakly-supervised learning have recently attracted considerable attention in the object detection literature since they can alleviate the cost of annotation needed to suc…
Facial Expression Analysis Using Decomposed Multiscale Spatiotemporal Networks
Wheidima Carneiro de Melo, Eric Granger, Miguel Bordallo Lopez
Video-based analysis of facial expressions has been increasingly applied to infer health states of individuals, such as depression and pain. Among the existing approaches, deep lea…
Dynamic Template Selection Through Change Detection for Adaptive Siamese Tracking
Madhu Kiran, Le Thanh Nguyen-Meidine, Rajat Sahay +3
Deep Siamese trackers have recently gained much attention in recent years since they can track visual objects at high speeds. Additionally, adaptive tracking methods, where target…
A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion Recognition
R. Gnana Praveen, Wheidima Carneiro de Melo, Nasib Ullah +8
Multimodal emotion recognition has recently gained much attention since it can leverage diverse and complementary relationships over multiple modalities (e.g., audio, visual, biosi…
Generative Target Update for Adaptive Siamese Tracking
Madhu Kiran, Le Thanh Nguyen-Meidine, Rajat Sahay +3
Siamese trackers perform similarity matching with templates (i.e., target models) to recursively localize objects within a search region. Several strategies have been proposed in t…
Negative Evidence Matters in Interpretable Histology Image Classification
Soufiane Belharbi, Marco Pedersoli, Ismail Ben Ayed +2
Using only global image-class labels, weakly-supervised learning methods, such as class activation mapping, allow training CNNs to jointly classify an image, and locate regions of…